# Demographics ofthe UK space sector

## Introduction

This report presents an overview of the demographic results of the 2020 Space Census, the first national survey of the UK space workforce.

Existing evidence, much of it anecdotal, has suggested that the space sector has diversity and inclusion problems, particularly around gender and ethnicity, but this evidence is limited. Without a good baseline it is hard to determine what interventions should be made, measure if these have any effect, and identify which are the most effective. The goal of the Space Census was therefore to collect baseline data to inform this work and feed into national policy and sector strategy. Data collected in future censuses will give a more detailed picture of trends within the sector.

These results are intended to complement those from the recent Space Sector Skills Survey and the upcoming edition of the Size and Health of the UK Space Industry report (to be published later this year).

Future reports will look in more detail at certain demographic groups (such as women), the intersections between different groups, and the non-demographic data that was also collected.

The 2020 Space Census was conducted by the Space Skills Alliance on behalf of the Space Growth Partnership's Space Skills Advisory Panel, and supported by the UK Space Agency and UKspace. It was funded by the University of Leicester.

## Methodology

The 2020 Space Census was conducted via an online form open for 12 weeks from 7th October to 31st December 2020.

It comprised approximately 50 questions covering demographic information (age, gender, ethnicity, etc.), work information (role, company, salary, etc.) experiences of discrimination, and paths into the sector (qualifications, influences, etc.). The demographic questions were designed to cover 8 of the 9 characteristics protected under the Equalities Act 2010. Marital status was not covered.

### Audience & sample size

The target audience was people working in the UK space sector in any capacity. This included those working in industry, academia (including PhD students, but not undergraduates), the military, government, and the non-profit sector, whether in a space-specific role (eg. satellite engineer) or not (eg. marketing).

Our target sample size was 1,000 people, which we estimated would give a reasonable level of accuracy for small populations such as ethnic minority groups. In the end we received 1,552 responses (not including a couple of spam responses offering us excellent deals on vaping products). The total space workforce is estimated to be about 42,000. However, this figure includes about 20,000 people working in direct-to-home (DTH) broadcasting, which is generally considered separate from the rest of the sector 1.

The non-DTH space workforce is estimated to be about 22,000, and an additional 7,000–10,000 work in academia (this is our rough estimate based on HESA data), so we estimate the population we are sampling to be about 30,000 people. Our sample is about 5% of that.

While the overall sample size is large enough to give us a high level of confidence in the accuracy of the findings, when looking at intersections of certain characteristics (for example sexuality and ethnicity), the sample sizes are considerably smaller. In these cases it is difficult to draw robust conclusions from the data, but it is useful in giving indications of trends and identifying areas for further research.

Though every effort was made to ensure that the we collected responses from across the whole sector, there is likely to be some bias in our dataset. These biases are discussed and estimated in Appendix A, and a breakdown of the characteristics of the response dataset is provided in Appendix C.

### Question design

A copy of all the questions is provided in Appendix B

The questions were agreed by the Space Skills Alliance and the Space Skills Advisory Panel’s diversity working group, and designed to help identify what steps should be taken to improve the UK space sector.

All questions were optional. The majority were closed questions, but there were also free-form text boxes for respondents to provide additional information if they wanted to.

The wording of certain sensitive questions on topics such as gender identity, ethnicity, and disability, was chosen to follow best practice set out by relevant groups such as Stonewall, the Office for National Statistics, and the Government Statistical Service.

The Space Census was presented as a single-page form, designed following Government Digital Service best practice and with a focus on accessibility and compatibility with a wide range of web browsers. Details of the technical implementation will be described in a future article.

### Promotion

The survey was shared by direct email with every organisation on the Knowledge Transfer Network’s list of space organisations 2, in email newsletters and social media posts sent out by a number of partner organisations, and at several space events. A list of organisations that assisted with promotion can be found in the acknowledgements.

### Non-response rate

Overall the non-response rate was very low, about 1% for the vast majority of questions. The exceptions were for more sensitive/identifiable responses such as organisation name (18%), salary band (5%), and location (5%). Qualification subject also had a high non-response rate (5%), possibly because it was a freeform field rather than a tickbox.

In most cases we have omitted non-responses and normalised the remaining responses to 100%. The exception is where the size of the non-response rate was comparable to the size of a valid response (for example trans identity).

### Processing and analysis

Light processing was done to the responses to make them analysable. Details of this processing and error analysis are provided in Appendix A.

We also compare the Space Census results to those from the engineering, technology, and science & maths workforces, and the wider UK population, primarily using data from the Office for National Statistics. These comparison datasets are referenced throughout the report. For the purposes of comparisons, all results have been normalised to 100% to exclude non-responses.

## Results

### Gender

Women are under-represented in the space sector. This is a common result across almost all STEM-heavy fields, as illustrated above. The space sector appears to fall somewhere around the average of the STEM fields, which may reflect its cross-disciplinary nature.

Women are more likely to come from outside the UK. They make up 37% of European nationals, 33% of Americans, and 41% of those from the rest of the world, compared to just 27% of British nationals. This tallies with statistics which show that the UK has the lowest proportion of female scientists and engineers in Europe 6.

We will examine the data on women in the space sector in more detail in a future report.

#### Trans identity

There are virtually no precise figures for the size of the trans population in the UK. This stems from the lack of a clear definition of who is included within the definition of trans 8 and how best to ask about it in surveys (Stonewall for example offers two different questions that identify slightly different groups 9). The ONS has not previously included trans identity in their surveys, but will do so for the first time this year. As a result, it is difficult to make comparisons between surveys and datasets.

Based on the estimates that are available, the proportion of trans people within the space sector appears to be in line with the population as a whole, but perhaps smaller than that in the physics workforce. However, these numbers should be treated with caution since the sample size is so small and the proportion of people who declined to answer this question is about the same as those who identified as being trans.

Of those who identified as trans, 60% identified as having a gender other than male or female, and 27% are not comfortable being open about their gender transition at work.

#### Gender by organisation type

There are significant differences in gender split by type of organisation; the figures are much more balanced within non-profits, government, and academia than for industry or the military.

These results largely follow well-documented trends. Women are more likely to work in non-profits and the public sector, and this has been associated with more inclusive and family-friendly practices in those sectors 10 11. Our previous work assessing space sector job adverts 12 has also found that public sector job adverts (including academia but not the military) tend to be more aligned with best practice shown to attract women.

The military by contrast is strongly associated with men and traditional masculinity 13, and, up until 2018, restricted the roles that women could hold 14. Women currently make up 11% of the wider military 15, but the new US Space Force looks set to improve that statistic 16.

#### Gender by age

The sector’s gender balance also varies considerably by age-group, with younger age groups generally closer to parity than older ones.

This may indicate that the gender balance in the sector is improving, or it may be an example of a phenomenon known as the ‘leaky pipeline’, common in STEM fields, in which women drop out of the workforce as they get older 17, usually in order to care for children 18 or because of hostile working environments 19. With only one data point we cannot yet determine whether the improvements to gender balance seen in the youngest cohorts will be maintained as they age.

We know that women are less likely to study STEM subjects at university, and that a substantial majority (89%) of people within the sector are university graduates, so the statistics above are likely to be to a large extent a reflection of this. We can estimate the size of this impact using the gender diversity figures for the most common subjects studied in the space sector (see Appendix A for full methodology). All things being equal we would expect 23–33% of young people entering the sector to be women. This range is considerably lower than what we see across almost all age groups, suggesting that the sector is doing a good job of recruiting women.

The 35–39 group bucks the trend, with a significantly larger proportion of women (40%) compared to either 30–34 year-olds (33%) or 40–44 year-olds (32%). It is likely that this result is due to a combination of effects: first, that women tend to leave the workforce to care for children in their early 30s (the median age of a degree-educated first-time mother is 28–30 20) and then return in their late 30s 21; second, that a similar but age-shifted phenomenon occurs for men, who are on average 3 years older when they have their first child 22.

### Parenting & Caring

#### Parenting

Overall, women are less likely to have parental responsibilities (24% vs 30% of men), suggesting that they are dropping out of the workforce when they have children, or choosing to have a career rather than a family (men are usually more able to have both 23).

However, looking at the breakdown by age, among 35–39 year-olds, women are almost twice as likely to have parental responsibilities (27 vs 15% of men), suggesting that some are rejoining the workforce after having had children.

#### Caring

6.1% of the space workforce care for a child or adult with an illness or disability compared to about 14.8% of the wider workforce 24. This statistic is pretty much equal across all genders and organisation types. Carers are twice as likely to be part time (20% vs 10% overall).

### Sexuality

LGBQ+ people appear to be well represented within the sector, with just over 10% of all respondents identifying as LGBQ+ (note that we discuss trans people in the gender section). Self-described sexualities (counted within ‘Other’) included queer, bicurious, pansexual, and polysexual.

Estimates for the proportion of LGBQ+ in the wider UK population are rough. The ONS figure (3.9%) presented above is generally taken to be a lower bound, with an upper bound estimated at about 7% 26.

#### Sexuality by organisation type

Government, academia, and non-profits have a much higher proportion (~14%) of LGBQ+ people compared to industry (7%) and the military (5%). Also notable is the absence of bisexual people in the military and the absence of homosexual people in non-profits. This may be a result of small sample sizes for these groups. It does not appear to be linked to the trend of young people being more likely to identify as bisexual.

#### Sexuality by age

Younger respondents were more likely to identify as LGBQ+, with 20% of 18–24 year-olds identifying as LGBQ+ compared to 5% of 45–49 year-olds. This matches results seen in other datasets of young people, such as RAS’ figures for astronomy postgraduate researchers 27 and UKSEDS’ figures for space students 28.

Younger respondents were also more likely to identify as bisexual as compared to gay or lesbian. This is a well recognised trend 29 thought to be a result of younger people being more open minded about sexuality 30.

#### Openness about sexuality

People are generally comfortable being open about their sexuality in the workplace, with 74% of LGBQ+ people saying they are open with their manager and/or colleagues (though many commented that they did not consider it a relevant topic for workplace discussion).

This contrasts significantly with the findings of the Royal Academy of Engineering’s 2017 survey, which found that only about 50% of LGBQ+ people felt that they could be open about their sexuality 31. It’s not clear why there is such a stark difference.

Those who identify as bisexual or a self-described sexuality are least likely to be open, but this does not appear to be related to the tendency for young people to identify as bisexual, as under 40s appear to be slightly more comfortable being open about their sexuality.

### Ethnicity

The space sector is mostly White (89%), and is slightly less diverse than the country as a whole (86%) but on par with the workforce (89%), with Black people significantly under-represented (1% vs 3% workforce) and Asian people over-represented (6% vs 4%). Across all groups the sector is on par with the physics workforce, and slightly more diverse than the engineering workforce.

Much of this diversity is a result of the inclusion of foreign nationals in the Space Census. Just over half of Black people come from outside the UK (18% Europe, 0% USA, 35% rest of world), and just over a third of Asians (2% Europe, 2% USA, 33% rest of world). White people are predominately British (84%) or European (13%).

There is no clear trend in variation of ethnic diversity by age. The most diverse age group by a large margin is 30–34 year olds (79% White vs 89% average), where Asian people in particular are significantly represented (12% vs 6% average). The least diverse group is 50–54 year-olds (95% White).

Though within the wider population younger people of working age tend to be more ethnically diverse 34, this is only partially seen for our ethnicity results. The youngest cohorts are on average more diverse than the older ones (84% White vs 93%), but that average conceals that 18–24 and 25–29 cohorts are less diverse (89% and 85% White) than the 30–34 cohort (79%). It is not clear why this is the case.

As we did for women, we can use university course diversity data to estimate how many people of ethnic minority backgrounds we might reasonably expect to find in the 18–24 cohort. We get a result of 3.2–4.5% Black, 8.0–11.4% Asian, and 4.0–5.7% of another minority ethnic background 35. The difference between these expected values and those we see for the 18–24 age group (6.6% Asian, 0% Black, 4.0% mixed or other) suggests that there is a ‘leak’ in the graduate pipeline for ethnic minority students, particularly Black students.

This may be a result of hiring from Russell Group universities, where only about about 3.3% of graduates are Black, compared to 6.6% across all universities. For Asian and other ethnic minorities by contrast, the percentages are about the same for both the Russell Group and all universities 36. We are not aware of any data on the proportion of Russell Group graduates recruited by the space sector.

#### Ethnicity by organisation type

Ethnic diversity varies by organisation type. The results are similar to those for gender diversity, with non-profits and universities more diverse than industry or the military, but on a smaller scale. The notable exception is government, which has significantly better gender diversity than academia, but significantly worse ethnic diversity.

Extreme care should be taken when comparing specific minority ethnic groups between organisation types, as the population sizes become very small. However, there is a notable difference in the representation of Asians, who are more likely to work in academia (7.7%) and non-profits (10.8%) than in any other sector (average 4.9%). This is a reflection of the nationality mix within these sectors. 27% of those working in academia and 23% of those at non-profits are foreign nationals, compared to a sector average of 18%.

Academia and the non-profit sector generally do not ask for UK nationality or security clearance, whereas this is more common within industry and government. Academia also has an international culture, characterised by short-term contracts, frequent moves between universities in different countries, special immigration rules such as research visas. About 12% of those in academia have lived in the UK for less than 5 years, compared to 7% in government and industry, and 3% in the military, and only 47% of Asians working in academia are British nationals, compared to 100% in the military, and 83% in government.

### Nationality

The sector has close ties with Europe. European nationals are mainly Italian (2.5%), Spanish (1.7%), Irish (1.6%), and French (1.4%). Of those from the rest of the world, the most common nationalities are Indian (1.0%), New Zealander (0.6%), Canadian (0.6%), and Australian (0.4%).

Almost two-thirds (64%) of Europeans have lived in the UK for at least 5 years (the minimum required to apply for permanent residency). By contrast, this is true for just a quarter (26%) of Americans, and just under half (48%) of those from the rest of the world.

Whether these ties will remain as strong post-Brexit we cannot yet say. Of European nationals, 12% are thinking of changing jobs because of immigration related issues such as Brexit, compared to 4% of the rest of the world, and 2% of British nationals.

### Disability

8% of people in the sector have some kind of disability. This is several percentage points lower than the both the STEM workforce workforce and the workforce as a whole (13% 37).

88% of disabled people in the sector describe their disability as low level, and 12% as significant. More women than men have a disability (11% vs 7%).

#### Specific disabilities

Statistics for specific types of disabilities are difficult to compare as the categories are rarely consistent between surveys.

The Space Census website was designed to be as accessible as possible for those using assistive devices such as screen-readers, so we are confident that there is not likely to be a significant bias in who was able complete it.

The most common reported disability is having mental health issues. This was particularly common among younger people (avg. 55% of 18–34 year-olds vs 23% of 35–49 year-olds), and women (55% vs 21% of men). These results align with trends seen nationally of a mental health crisis among young women 38.

#### Openness

Most disabled people are open about their disability with colleagues (57%) or their manager (29%), however women are half as likely to be open about their disability as men (20% vs 9%). Most of those who are not open have an ‘invisible’ disability such as mental health or a chronic pain condition.

### Socio-economic background

Socio-economic background is very difficult to assess effectively. It is typically measured using proxies such as childhood postcode, parental education, and type of secondary school. These each have advantages and disadvantages, but give a useful indication of trends. We asked about schooling because, of the recommended questions on this topic, it is generally the easiest to understand and receives the best response rates 39.

#### A note on the British school system for foreign readers

Most British schools can be classified as either state (state funded, run by various entities, free to attend, also known as maintained schools) or independent (privately run, parents pay fees, also known as private schools).

State schools can be further divided into selective (which either select students based on ability, in which case they are generally known as grammar schools, or on religion, in which case they are generally known as faith schools) and non-selective (which accept all students regardless of ability, and are generally known as comprehensives).

Most grammar schools were closed or converted to either comprehensive or independent schools under reforms in the 1980s. The term public school is misleading and refers to a historic group of independent schools. We apologise for having such a ludicrously complicated system.

The Space Census schooling figures are necessarily historic, so comparing them to current-day ones must be done with caution, as the proportion of different types of school has changed significantly over the past 50 years 42. Despite this, we see no significant variation with age in the proportion attending each school type, which gives us some confidence in making comparisons to current-day figures. The only variation of note is that young people in the space sector who attended an independent school are now much less likely to be recipients of a bursary compared to their older colleagues. This is despite the percentage of independent students receiving bursaries increasing slightly from 32% to 34% over the last 20 years. The overall bursary/non-bursary split in the Space Census results is about the same as it is in the population at large 41.

Those from more advantaged socio-economic backgrounds appear to be over-represented in the space sector. Of those who were UK-educated, people who attended private schools are over-represented by a factor of 2.2. Selective school attendees are over-represented by a factor of 4.6, while those attending comprehensives are under-represented by a factor of 0.7. There is no notable regional variation in our data set, despite grammar schools being more common in the South East today.

As we did for the gender and ethnicity figures, we can use university course data to estimate how many state and privately educated people we might reasonably expect to find in the 18–24 cohort (see Appendix for full methodology). Across all undergraduates, we would expect to see 7.8–11.2% coming from independent schools 43. The disparity between this figure and that reported (16%) suggests that independent school students are being preferentially hired, possibly from Russell Group universities where they make up about 23% of students, compared to 10% across all universities 44.

Most organisation types have very similar breakdowns of educational background. The main exception to this is the military, where people are more likely to come from non-selective rather than selective schools.

### Religion

The religious makeup of the sector is markedly different from the country as a whole, and even somewhat from the physics workforce, with two thirds (66%) professing no-religion, and a quarter (25%) following Christianity. Of the minority religions, Islam is the is the least well represented.

Young people are significantly less religious (9% of 18–24, 13% of 25–29 compared to 40% 50–54), in line with country-wide trends 45.

### Age

The sector skews slightly younger than both the workforce as a whole and other STEM sectors, but also includes more people aged 50+ than the technology sector. We find that this isn’t due to an age bias from sharing of the survey on social media (see Appendix A), but may actually be an indication of the impact of space outreach efforts and programmes such as Space Placements in Industry (SPIN) (mentioned by 4% of people aged 18–29) over the past 5+ years.

Though there has been some talk in the media of a retirement cliff in engineering causing problems for the future of space and other sectors 46 47, we do not see evidence of this in these results. This is in contrast to the results of a 2015 survey of the international space sector which found that 42% of the sector was over 55 years-old 48 – the equivalent figure for the UK sector is just 17%.

## Future work

This report is the first in a series that will examine the findings of the 2020 Space Census in detail. Further reports over the coming months will look at specific groups in more detail, examining topics such as the gender pay gap, experiences of discrimination and prejudice, and why people join and leave the space sector.

If you’d like to be informed when these are published, then subscribe to our newsletter or follow us on social media. If you have specific questions you would like us to explore in these reports, please get in touch with us at [email protected], and we will do our best to include them.

## Acknowledgements

We would like to thank the University of Leicester for funding the 2020 Space Census, and the Space Growth Partnership, UK Space Agency, and UK Space for providing resources and support for this research.

We would also like to thank those people and organisations who helped promote the Space Census, particularly the Satellite Applications Catapult, Space Universities Network (SUN), Royal Astronomical Society (RAS), the Space Academic Network (SPAN), SPRINT, SSPI UK, the British Association of Remote Sensing Companies (BARSC), the IET Satellite group, the British Interplanetary Society (BIS), Europlanet, the Space Generation Advisory Council (SGAC), GVF, World Space Week, and Space Park Leicester. We are also grateful to UKSEDS to for sharing their data on young people in the space sector.

A special thank you goes to Craig Brown and Kathie Bowden for their support in making the Space Census a reality, to our stalwart friends Rob Garner, Áine O’Brien, James Telfer, Portia Bowman, and Henry Lau for their advice, ideas, and typo-spotting eyes, and to our advisors Ed Chester, Julia Hunter-Anderson, and Sheila Kanani for their continued support of our work.

## Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You can copy, redistribute, and adapt what we’ve presented for any non-commercial purpose. However, you must give us credit and link back to this page. If you want to use it in a commercial context, get in touch with us at [email protected].

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## Appendix A: Processing & limitations

### Impacts of COVID-19 on the sample

The Space Census was conducted during the COVID-19 pandemic. We do not believe that the results have been noticeably impacted by this as the survey was conducted entirely online and there have not been significant COVID-related lay-offs in the sector 49.

### Age bias in the sample

The largest age group of respondents was 25–29, and as a whole our sample seems to skew slightly younger than other similar sectors.

We received almost a third of the responses over the first 3 days, following an initial rush of social media attention. We investigated whether this may have biased the responses towards younger respondents (who are most likely to use social media 50) by comparing the results received in the first three days to those received afterwards. We found that the social media driven responses were biased towards ‘younger’ age groups, but that the inflection point was at age 50.

Respondents younger than 40 were about 0.5% more likely to respond in the first three days. Those between 40 and 50 were about 3% more likely to respond, and those over 50 were about 2% less likely to respond. If social media did bias our responses, it appears to have biased them towards 40–50 year-olds rather than under 30s.

### UK regional bias in the sample

There is some significant variation between the geographical distribution of Census respondents and figures given by both the Knowledge Transfer Network’s space landscape directory 51 and the 2018 Size & Health report 1.

In particular the Space Census appears to over-represent people in the South East, and under-represent those in Scotland and in London.

This is likely due to a combination of us having better connections with organisations in the South East, particularly within the Harwell Space Cluster, and receiving relatively little response from Scottish space networks.

The under-representation of London is likely to be a result of people who would normally commute into London from the South East responding with their lockdown working location rather than where their employer is nominally based.

Region Space Census (% of respondents) KTN Space Landscape (% of organisations) 51 Size & Health (% of employees inc. DTH) 1
East Midlands 6.4 5.6 2.1
East of England 9.2 8.7 10.5
London 12.3 18.4 29.4
North East 1.0 2.9 2.2
North West 4.8 4.1 5.6
Northern Ireland 0.3 1.5 0.3
Scotland 5.0 9.4 18.1
South East 43.7 29.9 21.6
South West 11.1 10.4 3.2
Wales 1.3 3.5 1.2
West Midlands 2.5 3.0 2.8
Yorkshire and the Humber 2.4 2.6 3.1

#### Company size bias in the sample

We asked respondents to provide the size of the organisation they work in, with the options being micro (1–9 employees), small (10–49), medium (50–249), or large (250+), based on OECD definitions of business size 52. We did not reach out to DTH companies, which are all classed as large organisations, but are relatively few in number.

The Space Census appears to over-represent large and medium sized companies and under represent small ones. This is likely to be a result of the difficulty we had in reaching many small organisations.

Company size Space Census (% of respondents’ organisations) KTN Space Landscape (% of organisations) 51
Micro 34 35
Small 20 32
Medium 17 13
Large 30 20

#### Segment bias in the sample

We classified respondent’s organisations as upstream or downstream following the categorisation used in the UK Space Agency’s Size & Health report 1. Academic and ancillary organisations were not included.

The Space Census dataset is on par with the KTN dataset, but significantly biased toward upstream companies compared to the Size & Health data. This may be because downstream employees feel less connected to the space sector than other sectors like tech, and are therefore less likely to self-identify as the target audience of the Space Census.

Segment Space Census (% of respondents’ organisations) KTN Space Landscape (% of organisations) 51
Downstream 50 46
Upstream 50 54
Segment Space Census (% of respondents) Size & Health (% of employees ex. DTH) 1
Downstream 59 81
Upstream 41 19

### Removal of invalid responses

Of the 1,555 responses received, 3 were removed, leaving 1,552 responses for analysis. The 3 removed consisted of 1 blank response and 2 spam responses.

### Organisation type classification

Respondents were asked what type of organisation they worked for, selecting one of company, university, government (non-defence), government (defence), and non-profit, or providing a free-form answer. Just under 3% of respondents provided a free-form answer. We reclassified to one of the existing five categories, ‘self-employed’, or did not answer. Government (defence) is referred to in this report as military to distinguish it from the defence sector.

### Location classification

Respondents were asked where they lived, at a county level if living in the UK and a country level if living overseas. This field was a free-form box with a list of UK counties available in a dropdown. Most responses used one of the provided options. Where they did not, we reclassified first by country, and then by NUTS 1 region and county for UK responses, and state for US responses. A handful of responses were very vague and were classified as ‘world’.

### Subject classification

Respondents were asked which subject their highest qualification was in. This was a free-form box with some common answers available in a dropdown. Many responses were very specific, such as ‘Pure & Applied Chemistry: Collodial & Surface Science’.

We reclassified these first by principal subject (so the above became Chemistry) and then by subject area (Physical sciences), following the JACS 3.0 classification system 53.

### Calculation of errors

We calculated errors bars using the standard error $$e$$ for a finite population

$$e = {z \sqrt{{p(1-p) \over n} {N-n \over N-1}}}$$

where

• $$z$$ is the z-score, taken to be 1.96 for 95% confidence
• $$p$$ is the observed value
• $$n$$ is the sample size, taken to be 1552
• $$N$$ is the total population, taken to be 30,000 (see above)

### Estimating diversity from university admissions data

Because a substantial majority (89%) of people within the space sector have at least a first degree, its diversity is to some extent a reflection of the diversity of university graduates.

To estimate the impact that this might have, we can use diversity figures for physical science (encompassing physics, chemistry, geography and others 53), engineering, and computer science students 35, and then weight those groups by how common their subject is within the space sector.

This gives us the formula:

$$\hat{p}_c = s_d \times s_s \times s_c$$

where

• $$s_d$$ is the proportion of the space sector with a degree, which is 89%
• $$s_t$$ is the proportion of the space sector studying the subject
• $$t_c$$ is the proportion of the subject's students with the characteristic (ie. gender, ethnicity, etc.)

For example, Black students, this is:

Subject % of space sector with degree ($$s_d$$) % of space sector doing subject ($$s_t$$) % of subject's students who are Black ($$t_c$$) Estimate for space sector ($$\hat{p}_c$$)
Physical science 89 44 2.76 1.08
Engineering 89 29 6.92 1.79
Computer science 89 5.6 6.56 0.33
Total 3.19

This gives us a lower bound of 3.2%, having accounted for about 70% (89% x (44% + 29% + 5.6%)) of the people who enter the space sector. We can obtain an upper bound of 4.6% by assuming that the same proportions are true for all 100%.

## Appendix B: Question set

The entire question set, exactly as presented to respondents can be found here.

## Appendix C: Characteristics of the dataset

This appendix gives a breakdown of the characteristics of the Space Census responses used in this analysis.

### Breakdown by type of organisation

Breakdown of 2020 Space Census responses by type of organisation
Organisation Type %
Did not answer 1.0
Company 45.9
Military 4.2
Government 14.4
Non-profit 5.0
Self-employed 0.7

### Breakdown by size of organisation

Breakdown of 2020 Space Census responses by size of organisation
Organisation Size %
Did not answer 0.6
Large 61.8
Medium 18.7
Micro 8.4
Small 10.5

### Breakdown by location

Breakdown of 2020 Space Census responses by location
Location (UK responses only) %
Did not answer 1.4
East Midlands 6.2
East of England 9.1
London 12.2
North East 1.0
North West 4.8
Northern Ireland 0.3
Scotland 5.0
South East 43.1
South West 10.9
Wales 1.2
West Midlands 2.5
Yorkshire and the Humber 2.3

### Breakdown by job type

Breakdown of 2020 Space Census responses by job type
Role area %
Did not answer 0.8
Computing 7.2
Education 4.6
Engineering 26.1
Management 18.3
Other 5.4
Policy 3.0
Sales 6.4
Scientific 26.4

### Breakdown by organisation

81% of respondents provided the name of their organisations. In total 258 organisations were named. 1% of respondents said that they were self-employed or freelancers. The remaining 18% declined to answer.

A list of all of the organisations and the number of respondents from each one can be downloaded here.